Mean Temperature Distribution Research Articles

Temperatures, conflict and forced migration in West Asia and North Africa

The region of West Asia and North Africa has not only been termed a “hotspot” region for the adverse impact of climate change in light of extreme temperature increases. Several countries have also experienced protracted humanitarian crises and civil wars in the last two decades, such as those in Syria, Yemen and Libya. The vulnerability of these populations makes advancing our understanding of how climate change may impact migration patterns in the region a matter of urgency. This study examines whether extreme temperatures influence bilateral forced migration between countries within West Asia and North Africa through their potential to increase armed conflict. The findings suggest that extreme temperatures in two consecutive years, defined as the upper 10% of the country-specific annual mean temperature distribution, cumulatively increase the probability of armed conflict by 42.5% in the following year ( p = 0.07). Armed conflict is strongly associated with an increase in asylum flows, by 45.8 percentage points ( p = 0.00), and there is a weak indication that conflict mediates the relationship between extreme heat and asylum flows. This explorative study is the first to apply a regional displacement perspective to the climate-conflict-migration nexus in West Asia and North Africa. The results underline the importance of taking contextual factors into account in the analysis of environmental migration.

Spatiotemporal distribution and lag effect of extreme temperature exposure on mortality of residents in Jiangsu, China

BackgroundWith the ever-increasing occurrence of extreme weather events as a result of global climate change, the impact of extreme temperatures on human health has become a critical area of concern. Specifically, it is imperative to investigate the impact of extreme weather conditions on the health of residents. MethodsIn this study, we analyze the daily death data from 13 prefecture-level cities in Jiangsu Province from January 2014 to September 2022, using the distributed lag nonlinear model (DLNM) to comprehensively account for factors such as relative humidity, atmospheric pressure, air pollutants, and other factors to evaluate the lag and cumulative effects of extreme low temperature and high temperature on the death of residents across different age groups. Additionally, we utilize the Geographical Detector to analyze the effects of various meteorological and environmental factors on the distribution of resident death in Jiangsu Province. This provides valuable insights that can guide health authorities in decision-making and in the protection of residents. ResultsThe experimental results indicate that both extreme low and high temperatures increase the mortality of residents. We observe that the impact of extreme low temperatures has a delayed effect, peaking after 3–5 days and lasting up to 11–21 days. In contrast, the impact of extreme high temperature is greatest on the first day, and lasts only 2–4 days. ConclusionBoth extreme high and low temperatures increase the mortality of residents, with the former being more transient and stronger and the latter being more persistent and slower. Furthermore, residents over 75 years of age are more vulnerable to the effects of extreme temperatures. Finally, we note that the spatial distribution of resident deaths is most closely associated consistent with the spatial distribution of daily mean temperature, and there is significant spatial heterogeneity in deaths among residents in Jiangsu Province.

A method for estimating the effect of climate change on monthly mean temperatures: September 2023 and other recent record‐warm months in Helsinki, Finland

AbstractWe describe a method for quantifying the contribution of climate change to local monthly, seasonal, and annual mean temperatures for locations where long observational temperature records are available. The method is based on estimating the change in the monthly mean temperature distribution due to climate change using CMIP6 (Coupled Model Intercomparison Project Phase 6) model data. As a case study, we apply the method to the record‐warm September 2023 in Helsinki, and then briefly examine all record‐warm months of the 21st century. Our results suggest that climate change made the record‐warm September in Helsinki 9.4 times more likely and 1.4°C warmer. Thus, the new monthly mean record in September 2023 would probably not have been set without the observed global warming. The presented and provided tool allows operational meteorologists and climatologists to monitor and report the impact of climate change on local temperatures in near real time.

Risk of ischemic and hemorrhagic stroke in relation to cold spells in four seasons

BackgroundCold winter weather increases the risk of stroke, but the evidence is scarce on whether the risk increases during season-specific cold weather in the other seasons. The objective of our study was to test the hypothesis of an association between personal cold spells and different types of stroke in the season-specific context, and to formally assess effect modification by age and sex.MethodsWe conducted a case-crossover study of all 5396 confirmed 25–64 years old cases with stroke in the city of Kaunas, Lithuania, 2000–2015. We assigned to each case a one-week hazard period and 15 reference periods of the same calendar days of other study years. A personal cold day was defined for each case with a mean temperature below the fifth percentile of the frequency distribution of daily mean temperatures of the hazard and reference periods. Conditional logistic regression was applied to estimate odds ratios (OR) and 95% confidence intervals (95% CI) representing associations between time- and place-specific cold weather and stroke.ResultsThere were positive associations between cold weather and stroke in Kaunas, with each additional cold day during the week before the stroke increases the risk by 3% (OR 1.03; 95% CI 1.00–1.07). The association was present for ischemic stroke (OR 1.05; 95% CI 1.01–1.09) but not hemorrhagic stroke (OR 0.98; 95% CI 0.91–1.06). In the summer, the risk of stroke increased by 8% (OR 1.08; 95% CI 1.00–1.16) per each additional cold day during the hazard period. Age and sex did not modify the effect.ConclusionsOur findings show that personal cold spells increase the risk of stroke, and this pertains to ischemic stroke specifically. Most importantly, cold weather in the summer season may be a previously unrecognized determinant of stroke.

Experimental study for comparison of thermal comfort and air age between two combined ventilation systems with chilled ceiling considering occupant density

AbstractDue to the global spread of diseases and epidemics, the need to maintain a clean indoor atmosphere has received increasing attention in recent years. Therefore, there will be a need to clearly estimate and define the areas that affect human exposure to pollutants, taking into account the occupied density, which is the primary importance of this research. The capacity of the chilled ceiling combined with mixing ventilation and personal ventilation systems has been studied and compared to the chilled ceiling with mixing ventilation in terms of mean air age, temperature distribution, CO2 concentration, and thermal efficiency, with the best flow rate of the proposed system considering the occupied density in a thermally insulated office room experimentally in the climate of Iraq (Hilla, a hot and dry climate). Twelve tests were performed for four different cooling loads with cooled ceilings (0%, 0.25%, 50%, and 80%), at a constant supply air flow rate with two PV airflow modifiers for three cases. As the cooling load treated by a chilled ceiling increased, the average air temperature increased with height in all cases. The lowest values of average air age appeared in the occupied area in the case of a chilled ceiling with mixing ventilation. This study shows that the chilled ceiling combined with a mixing ventilation and personal ventilation system with a flow rate of 7.5 L/s provides thermal comfort and higher air quality in the occupied area. based on the values of air exchange efficiency and occupants’ air exchange efficiency. As a result, a flow rate of 7.5 L/s is the best option for protecting occupants from direct pollution in the breathing zone and in the surrounding microclimate, because the lower the ventilation rate, the less air is changed for occupants.

Effects of High Temperature on COVID-19 Deaths in U.S. Counties.

The United States of America (USA) was afflicted by extreme heat in the summer of 2021 and some states experienced a record-hot or top-10 hottest summer. Meanwhile, the United States was also one of the countries impacted most by the coronavirus disease 2019 (COVID-19) pandemic. Growing numbers of studies have revealed that meteorological factors such as temperature may influence the number of confirmed COVID-19 cases and deaths. However, the associations between temperature and COVID-19 severity differ in various study areas and periods, especially in periods of high temperatures. Here we choose 119 US counties with large counts of COVID-19 deaths during the summer of 2021 to examine the relationship between COVID-19 deaths and temperature by applying a two-stage epidemiological analytical approach. We also calculate the years of life lost (YLL) owing to COVID-19 and the corresponding values attributable to high temperature exposure. The daily mean temperature is approximately positively correlated with COVID-19 deaths nationwide, with a relative risk of 1.108 (95% confidence interval: 1.046, 1.173) in the 90th percentile of the mean temperature distribution compared with the median temperature. In addition, 0.02YLL per COVID-19 death attributable to high temperature are estimated at the national level, and distinct spatial variability from -0.10 to 0.08years is observed in different states. Our results provide new evidence on the relationship between high temperature and COVID-19 deaths, which might help us to understand the underlying modulation of the COVID-19 pandemic by meteorological variables and to develop epidemic policy response strategies.

Improving the detectability and confirmation of hidden surface corrosion on metal sheets using active infrared thermography

This research aims to provide a simple approach to detecting and determining hidden corrosion using active infrared thermography with improved consistency in distinguishing hidden defect areas of metal sheets (galvanized steel and stainless steel) commonly used as part of building envelopes. Early studies on detecting hidden defects focused primarily on defects resulting from material loss. Equally important is the early detection of corroded metal surfaces hidden from the observer's plane of view through non-invasive means. In this study, two heating configurations using portable heaters were explored, along with two analysis approaches to aid in detecting and confirming the presence of hidden corroded surfaces. Metal sheets with or without hidden surface corrosion are detected, distinguished, and confirmed by observing differences in their mean surface temperatures and temperature distribution. The detection and confirmation involve two simple analysis approaches: (1) observing the differences in mean surface temperature and visual thermal contrast of the non-corroded surface available for monitoring during the heating-cooling cycle; and (2) comparing the distribution of temperature probability at a given temperature. The new method is considerably more practical as it would require only heating the region of interest to a temperature of no more than 70 °C using a portable heat source and detailed analysis requiring temperature distribution between 40 and 70 °C. The results from the detection and confirmation approaches also conform with basic principles of heat transfer, making the detection and analysis method not only practical but also scientifically sound. This method may potentially be adopted in building surveys, early detection, and post-monitoring of hidden corroded surfaces that may impact building envelope deterioration and structural integrity.

Ambient temperature and nervous system diseases-related mortality in Japan from 2010 to 2019: A time-stratified case-crossover analysis

BackgroundDespite the substantial disease burden caused by nervous system diseases, few studies have examined the association between ambient temperature and nervous system diseases, especially during cold seasons. Evidence for specific disease subgroups such as Alzheimer's and Parkinson's is also lacking. ObjectivesThis study examined the association between short-term changes in ambient temperature and nervous system diseases-related mortality in ten Japanese prefectures from 1 January 2010 to 31 December 2019. MethodsA two-stage analysis based on a time-stratified case-crossover study design was conducted. A conditional quasi-Poisson regression model with a distributed lag non-linear model for temperature was applied followed by a multivariate random-effects meta-analysis to obtain average associations. Mortality due to all and cause-specific nervous system diseases (major neurodegenerative diseases, Alzheimer's, and Parkinson's) were analyzed, with consideration for sex and age (0–84 and 85+ years old) subgroups. ResultsWe analyzed 162,315 death cases due to nervous system diseases. Cold was associated with all categories of nervous system diseases-related mortality, but not heat. The estimated relative risks for cold, obtained by comparing the 2.5th percentile of daily mean temperature distribution to the minimum mortality temperature (MMT), were 1.43 (95 % CI: 1.28–1.60), 1.37 (95 % CI: 1.17–1.59), 1.53 (95 % CI: 1.07–2.01), and 1.54 (95 % CI: 1.13–2.10) for all nervous system diseases, major neurodegenerative diseases, Alzheimer's, and Parkinson's, respectively. These associations were also observed in the sex and age subgroups in general but without evidence of effect modification. Heat (the 97.5th percentile of daily mean temperature distribution vs. MMT) was associated with Parkinson’s disease-related mortality among those aged 85 years and over. DiscussionCold was associated with an increased risk of nervous system disease-related mortality. The effect of heat was not observed, except for mortality among the elderly aged 85 years and older with Parkinson's disease.

Analytical solutions for the acoustic field in thin annular combustion chambers with linear gradients of cross-sectional area and mean temperature

Predictions of thermoacoustic instabilities in annular combustors are essential but difficult. Axial variations of flow and thermal parameters increase the cost of numerical simulations and restrict the application of analytical solutions. This work aims to find approximate analytical solutions for the acoustic field in annular ducts with linear gradients of axially non-uniform cross-sectional area and mean temperature. These solutions can be applied in low-order acoustic network models and enhance the ability of analytical methods to solve thermoacoustic instability problems in real annular chambers. A modified WKB method is used to solve the wave equation for the acoustic field, and an analytical solution with a wide range of applications is derived. The derivation of the equations requires assumptions such as low Mach number, high frequency and small non-uniformity. Cases with arbitrary distributions of cross-sectional surface area and mean temperature can be solved by the piecewise method as long as the assumptions are satisfied along the entire chamber.

Mean Flow, Turbulent Structures, and SPOD Analysis of Thermal Mixing in a T-Junction with Variation of the Inlet Flow Profile

This paper investigates the effects of different inlet flow profiles on thermal mixing within a T-junction using CFD simulations with the IDDES-SST turbulence model. The different combinations of inlet flow profiles are related to different stage in the flow entry region. The effects of the inlet flow profile on the mean and transient flow behaviour are assessed, while a spectral proper orthogonal decomposition and power spectral density analysis are performed to assess the underlying flow structures and the predominant frequency modes. It is found that the vortical structures associated with the horseshoe and hovering vortex systems consist of a single roll-up vortex for cases with uniformly distributed boundary conditions (BCs) at the branch inlet whereas a double roll-up vortex is observed for the other cases. The double roll-up vortex enhances the mixing locally due to the entrainment of fluid from the branch pipe in these vortical structures, which then results in a lower mean temperature distribution. The appearance of the secondary vortex pair and the nested vortices is delayed for cases with uniformly distributed BCs at the branch inlet, which again results in lower thermal mixing and consequently higher values of mean temperature when compared with the other cases. It is also found that the vorticity related to the counter-rotating vortex pair as well as to the second pair of vortices rotating in the opposite direction is higher for cases with uniformly distributed BCs at the branch inlet. Lastly, the combinations of inlet flow profiles lead to different coherent structures, and the dominant frequencies are of a Strouhal number of around 0.7 for uniformly distributed profiles at the branch inlet and in the range 0.4–0.5 for the other cases.

Transitional fluctuations of thermal boundary layer in horizontal convection

Fluctuations of thermal boundary layer (BL) in horizontal convection (HC) strongly affect the global heat transport through the HC sample and predominately determine the flow state. Here, we present a systematic experimental study of vertical profiles of mean temperature and temperature variance in the thermal BL of a HC flow that are heated and cooled from the bottom. Three rectangular HC samples filled with de-ionised water are used in the experiment. They have the same aspect ratios Γ≡L:W:H=10:1:1 but with different L (L, W and H are, respectively the length, width and height of the sample). The Rayleigh number Ra varies in the range 2×1010≲Ra≲1.3×1013, and the Prandtl number Pr is in the range 3.9≲Pr≲6.5. For all Ra in the studied range, we find that the cold thermal BL above the cooling plate remains laminar and the vertical profiles of measured mean temperature follow a universal scaling form predicted for laminar BL by Yan, Shishkina and He (J. Fluid Mech., vol. 915, 2021, R5). Above the heated plate, on the contrary, temperature fluctuations in the hot thermal BL undergo several transitional changes as Ra increases. For Ra≲6×1010, the thermal BL has a stable double-layer structure agreeing with the predicted scaling form for laminar BL and the temperature fluctuations are nearly zero. In the range 6×1010≲Ra≲1.1×1011, temperature fluctuations inside the BL have intermittent decayed oscillations, which results in deviations of the measured mean temperature profiles from the predicted scaling form. For 1.1×1011≲Ra≲1012, the temperature oscillations inside the BL become continuous and stable. Correspondingly, an intermediate layer emerges in the thermal BL, where the mean temperature profile has a sinusoidal variation on the distance z above the heated plate. For 1012≲Ra≲1.3×1013, the temperature fluctuations in the intermediate layer become irregular and intermittent, indicating a growing mixing intensity as Ra increases. When Ra exceeds 7×1012, the vertical distribution of mean temperature in the intermediate layer is uniform because of strong mixing. The temperature-variance vertical profiles follow a power-law function σT2(z)∼z−γ with the exponent γ=0.66, which agrees with the Priestley prediction for thermal convection over a heated horizontal surface. Our results thus reveal a series of transitional changes of temperature fluctuations, from laminar to chaotic states, in the hot thermal BL. They predominately account for the enhancement of global heat transport in the HC flow observed by Reiter and Shishkina (J. Fluid Mech., vol. 892, 2020, R1).

Study of a lead-bismuth eutectic jet issued into a heated cavity using large eddy simulation

Low Prandtl number convection of an axisymmetric turbulent lead-bismuth eutectic (LBE) jet discharged into a heated confined geometry using large eddy simulation is investigated. The Reynolds number based on jet centerline velocity and jet diameter is Re = 44,706. The results demonstrate some features of liquid metal that deviate from those of ordinary fluids. Examples include the differences between fluctuations of temperature and velocity, the distributions of turbulent viscosity and turbulent diffusivity of heat, and the misalignment between the turbulent heat flux vector and the gradient of mean temperature, all of which imply that standard turbulence models may not be suitable for the simulation of such flows. The LBE jet at Pr = 0.03 is compared with a high-pressure water jet at Pr = 0.8 under the same Re and Fr. The centerline decay of the mean velocity for LBE demonstrates the same behavior as that of water, which is governed by a linear variation for the self-preservation region between 1.5D and 8.5D, where D is the diameter of the jet orifice. In contrast, the centerline mean temperature for LBE decreases slower compared with that of water. The difference in temperature results from the high intensity of molecular diffusion in heat transport in LBE, while the momentum transport is mainly by turbulent diffusion in both flows. Self-preserving characteristic of temperature r.m.s (Trms) is observed. The radial profiles of Trms are presented by an axisymmetric curve with a maximum at around 0.7b, where b is the half-value radius of Trms. Good agreement of mean temperature distribution between the simulation results and the experiments are obtained.

Impact of cold spells on COPD mortality in Jiangsu Province, China.

Ambient cold is associated with substantial population attributable fraction of mortality in China, and respiratory health is vulnerable to cold exposure. This study aimed to examine the effect of cold spells on risk of deaths from chronic obstructive pulmonary disease (COPD). We collected daily data on deaths from COPD and climatic factors from 1 January 2016 to 31 December 2019 in 13 cities of Jiangsu Province, China. We used a quasi-Poisson generalized linear model coupled with a distributed lag non-linear model to quantify the association between risk of COPD deaths and exposure to cold spells (defined as 2 or more consecutive days with mean temperature ≤ 5th percentile of daily mean temperature distribution in cold months). Stratification analyses by age, sex, education, and occupation were undertaken to identify vulnerable subgroups. The results suggested that exposure to cold spells was associated with a higher risk of COPD deaths in Lianyungang (relative risk (RR): 1.70; 95% confidence interval (CI): 1.31, 2.21), Nanjing (RR: 1.54; 95% CI: 1.16, 2.04), Nantong (RR: 1.97; 95% CI: 1.68, 2.31), Suzhou (RR: 1.97; 95% CI: 1.55, 2.50), Suqian (RR: 1.68; 95% CI: 1.23, 2.29), Taizhou (RR: 1.70; 95% CI: 1.32, 2.19), Wuxi (RR: 1.99; 95% CI: 1.53, 2.60), Xuzhou (RR: 1.71; 95% CI: 1.01, 2.90), Yancheng (RR: 1.78; 95% CI: 1.53, 2.06), Yangzhou (RR: 2.78; 95% CI: 2.06, 3.76), and Zhenjiang (RR: 1.79; 95% CI: 1.26, 2.55). All subgroups seemed to be vulnerable to the effect of cold spells. The recommendation of this study is that individuals with pre-existing COPD, regardless of age, sex, education, or occupation, should be made aware of the health risk posed by cold spells and should be encouraged to take cold adaptation actions before cold season arrives. The main limitation of this study is that it is subject to ecological fallacy.

Analysis of Fire Throttling in Longitudinally Ventilated Tunnels With a One-dimensional Model

Fire throttling is the increase in flow resistance due to a large fire in a longitudinally ventilated tunnel. Although the fire throttling effect has been been known and studied for tunnels over the last 40 years, there is not yet a consistent one-dimensional (1D) model that can describe this behaviour or a framework suitable for practical application. We propose a semi-empirical model, based upon pipe flow engineering principles, to describe this effect by separating the resistance to flow, or pressure loses in three parts: upstream of the fire, locally at the fire, and downstream of the fire. The proposed 1D model called TE1D is derived from a simple steady one-dimensional momentum balance in which a semi-empirical mean temperature distribution is assumed across the tunnel. We verify the model by comparing the pressures losses it predicts with those calculated in CFD simulations based on OpenFOAM and Fire Dynamics Simulator. The comparison shows good agreement between the CFD codes for the range of fires sizes considered from 5 to 50 MW and good agreement between TE1D and the CFD results with the proposed 1D model for fire sizes below 30 MW. However, for values above there are large discrepancies between the results obtained by the TE1D and CFD. We posit as a potential explanation that these differences are due to flow and temperature stratification which is not accounted for in the 1D model. The model using pipe flow principles allows engineers to adopt this model for design, together with other pressure losses considered in tunnel ventilation.

Evaluation of Long-Term and High-Resolution Gridded Precipitation and Temperature Products in the Qilian Mountains, Qinghai–Tibet Plateau

Long-term and high-resolution gridded products of precipitation and temperature data are highly important to study the changes in climate and environment under global warming. Considering the uncertainties of these products in mountainous areas, it is necessary to evaluate the data reliability. This study evaluates the performances of the CMFD (China Meteorological Forcing Dataset) and ERA5-Land in simulating precipitation and temperature in the Qilian Mountains over the period of 1980–2018. We use the observation data of 28 basic meteorological stations in the Qilian Mountains to compare with the reanalysis products. Error metrics (the correlation coefficient (CC), the root mean square error (RMSE), the mean absolute error (MAE), and the relative bias (BIAS)) are used to quantify the monthly differences in existence between the observed data and reanalysis data. Our findings indicate that both CMFD and ERA5-Land could well reproduce the spatial distribution of mean monthly precipitation and temperature in the region. A good correlation is found between CMFD and OBS under different amounts of monthly precipitation conditions. The monthly average temperatures of CMFD and ERA5-Land reveal a high correlation with the observed results. Moreover, the CC values of CMFD and ERA5-Land precipitation products are the highest in autumn and the lowest in winter, and the CC values of both CMFD and ERA5-Land temperature products are higher in spring and autumn. However, we find that both reanalysis products underestimate the temperature to varying degrees, and the amount of precipitation is overestimated by ERA5-Land. The results of the evaluation show that the errors in precipitation yielded by CMFD as a whole are distinctly fewer than those yielded by ERA5-Land, while the errors in air temperature yielded by both ERA5-Land and CMFD are nearly identical to each other. Overall, ERA5-Land is more suitable than CMFD for studying the trends of temperature changes in the Qilian Mountains. As for simulation of precipitation, CMFD performs better in the central and eastern parts of the Qilian Mountains, whereas ERA5-Land performs better in the western part of the Qilian Mountains.

A Comparative Study of Models for Heat Transfer in Bidisperse Gas–Solid Systems via CFD–DEM Simulations

In this study, flow and heat transfers in bidisperse gas–solid systems were numerically investigated using the computational fluid dynamics–discrete element method (CFD–DEM). Three different models to close the gas–solid heat transfer coefficient for each species of bidisperse systems were compared in the simulations. The effect of the particle diameter ratio and particle number ratio between large and small particles on the particle mean temperature and temperature distribution of each species were systematically investigated. The simulation results show that differences in the particle mean temperature and temperature distribution profiles exist among the three heat transfer models at a higher particle number ratio. The differences between the effects of three heat transfer models on heat transfer properties in bidisperse systems with particle diameter ratios of up to 4 are marginal when the particle number ratio between small and large particles is 1.

Nonstationary seasonal model for daily mean temperature distribution bridging bulk and tails

In traditional extreme value analysis, the bulk of the data is ignored, and only the tails of the distribution are used for inference. Extreme observations are specified as values that exceed a threshold or as maximum values over distinct blocks of time, and subsequent estimation procedures are motivated by asymptotic theory for extremes of random processes. For environmental data, nonstationary behavior in the bulk of the distribution, such as seasonality or climate change, will also be observed in the tails. To accurately model such nonstationarity, it seems natural to use the entire dataset rather than just the most extreme values. It is also common to observe different types of nonstationarity in each tail of a distribution. Most work on extremes only focuses on one tail of a distribution, but for temperature, both tails are of interest. This paper builds on a recently proposed parametric model for the entire probability distribution that has flexible behavior in both tails. We apply an extension of this model to historical records of daily mean temperature at several locations across the United States with different climates and local conditions. We highlight the ability of the method to quantify changes in the bulk and tails across the year over the past decades and under different geographic and climatic conditions. The proposed model shows good performance when compared to several benchmark models that are typically used in extreme value analysis of temperature.

Relationship between the breeding distribution of forest birds and annual mean temperature based on two national surveys in Japan

Relationship between the breeding distribution of forest birds and annual mean temperature based on two national surveys in Japan

Climate Variability and Trend Analyses of Rainfall and Temperature Data of Imphal, Manipur

Understanding local climate variability and change is necessary for improving future climate forecasts and also aids preparation of informed area specific climate mitigation and adaptation strategies. Climate change at local scale is best revealed by studying observed variabilities and trends in rainfall and temperature data through statistical techniques. Therefore, this study employed standard deviation and coefficient of variability and Mann-Kendall test and Sen slope determination non-parametric techniques to perform variability and trends analyses across multiple temporal scales on climate data obtained at Imphal (Tulihal) station. The results indicate prevalence of different patterns between rainfall and temperature trends. Except for the positive trends in the month May (2mm/yr) and in the pre-monsoon season (9.49mm/yr), no other discernable patterns in rainfall data were observed. Temperature trends, on the other hand, witnessed significant positive increase in maximum, minimum and mean values. For mean temperature, all months registered significant increasing trends. At the annual and seasonal scales also, maximum, minimum and mean temperatures have increased although with varying rates. It is noteworthy to mention that temperature change has occurred at two distinct phases; before 1993 slow warming and after 1993 rapid warming. Temporal distribution of annual mean temperature captures this pattern more vividly as warming rate before 1993 was less than 0.01 compared to 0.450c/year in the latter phase. Overall, it can be said that rainfall has higher variability with very little or no pattern but temperature distribution suggests existence of strong trends in the observed data.

The effect of inlet flow conditions upon thermal mixing and conjugate heat transfer within the wall of a T-Junction

This paper investigates the effects of different inlet velocity profiles on thermal mixing and conjugate heat transfer (CHT) within a T-junction. The flow domain is modelled using the Improved Delayed Detached Eddy Simulation (IDDES) turbulence model implemented within the commercial CFD software STAR-CCM+ 2020.1.1. The thermal analysis of the solid domain is also addressed within the CFD simulations. The OECD/NEA-Vattenfall experimental benchmark database is used to validate the CFD model. The effect of mesh sensitivity within the CFD simulations is also studied qualitatively and quantitatively. The influence of different inlet flow profiles on the CFD simulations is then assessed. Different combinations of inlet flow profiles, uniformly distributed and fully developed, are considered. Compared to the flow profile at the main pipe inlet, the flow profile at the branch pipe inlet presents a much more significant effect on the mean temperature distribution downstream of the T-junction. It is found that the flat flow profile at the branch inlet causes a higher temperature at the top wall, therefore a larger temperature gradient, and may lead to higher thermal stresses due to thermal stratification. The temperature distribution is more uniform for cases with the fully developed flow profile at the branch inlet. The variance of temperature is high at the sides of the pipe, regardless of the velocity profile used. The combination of flat flow profiles at both inlets causes the highest temperature variance. Moreover, the regions of maximum variance of temperature are located at different positions along the pipe section, depending on the combinations of inlet flow profiles.